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231225s2019 xx |||||o 00| ||eng c |
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|a 10.1029/2019GL082236
|2 doi
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|a DE-627
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|a eng
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| 100 |
1 |
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|a Cui, Zhiqiang
|e verfasserin
|4 aut
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| 245 |
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|a A Preliminary Impact Study of CYGNSS Ocean Surface Wind Speeds on Numerical Simulations of Hurricanes
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|c 2019
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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| 338 |
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|a ƒa Online-Ressource
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|2 rdacarrier
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|a Date Revised 12.10.2023
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|a published: Print-Electronic
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|a Citation Status PubMed-not-MEDLINE
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|a The NASA Cyclone Global Navigation Satellite System (CYGNSS) was launched in December 2016, providing an unprecedented opportunity to obtain ocean surface wind speeds including wind estimates over the hurricane inner-core region. This study demonstrates the influence of assimilating an early version of CYGNSS observations of ocean surface wind speeds on numerical simulations of two notable landfalling hurricanes, Harvey and Irma (2017). A research version of the National Centers for Environmental Prediction operational Hurricane Weather Research and Forecasting model and the Gridpoint Statistical Interpolation-based hybrid ensemble three-dimensional variational data assimilation system are used. It is found that the assimilation of CYGNSS data results in improved track, intensity, and structure forecasts for both hurricane cases, especially for the weak phase of a hurricane, implying potential benefits of using such data for future research and operational applications
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| 650 |
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|a Journal Article
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| 650 |
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|a CYGNSS
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| 650 |
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4 |
|a data assimilation
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| 650 |
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4 |
|a ocean surface winds
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| 650 |
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4 |
|a tropical cyclone
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| 700 |
1 |
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|a Pu, Zhaoxia
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Tallapragada, Vijay
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Atlas, Robert
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Ruf, Christopher S
|e verfasserin
|4 aut
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| 773 |
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|i Enthalten in
|t Geophysical research letters
|d 1984
|g 46(2019), 5 vom: 16. März, Seite 2984-2992
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|x 0094-8276
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|g volume:46
|g year:2019
|g number:5
|g day:16
|g month:03
|g pages:2984-2992
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| 856 |
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|u http://dx.doi.org/10.1029/2019GL082236
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